code: def _estimate_column_wise_covariances(
      X: np.ndarray, Y: np.ndarray
  ) -> np.ndarray:
      return np.cov(X, Y, rowvar=False)[: X.shape[1], -Y.shape[1] :]
  
file_path: dowhy/dowhy/gcm/independence_test/kernel.py
imports: from typing import Callable, List, Optional, Union
  import numpy
  import scipy
  from causallearn.utils.KCI.KCI import KCI_CInd, KCI_UInd
  from joblib import Parallel, delayed
  from sklearn.preprocessing import scale
  import dowhy.gcm.config
  from dowhy.gcm.independence_test.kernel_operation import approximate_rbf_kernel_features
  from dowhy.gcm.stats import quantile_based_fwer
  from dowhy.gcm.util.general import auto_apply_encoders, auto_fit_encoders, set_random_seed, shape_into_2d
label_desc: Use image node_id 6 for calling a global function with example usage: _estimate_column_wise_covariances(X, Y) and returns: np